Languages are always evolving, because the needs they serve are always evolving. Stasis is death.
> I have been using ruby since 2005 or so. Static types were never relevant or needed in the slightest here.
We are like Liebniz monads, with disjoint views of the same universe due to our different experiences. I worked for several years at Shopify and there were droves of developers begging for types. Shopify itself recognized this need. We contributed early to Sorbet and began implementing it in the main monolith prior to it being publicly announced. I personally was the incident response on-call for a million-dollar bug that static typing would have prevented from ever being merged. And so on.
No, it's just a tool someone posted that's written in Ruby, with a strong signal that the authors are LLM proponents. It could have been a todo list and I'd still have the same question.
I didn't misunderstand what this library is about. I assume the authors are using LLM's to help author their code in general, even meta-frameworks like this.
Why would anyone still build in dynamically typed languages in 2026? Why relinquish the crystal clear signals that static typing is able to provide to the LLM?
More generically, our species' Achilles heel is our inability to factor in the long-term cost of negative externalities when evaluating processes that yield short-term positive results.
Counterargument. The author is primarily looking at AI trend lines. Let's say our industry continues moving along alternate, equally compelling, trend lines: increasing global volatility, chaos in the energy markets, growing likelihood of great power conflict this century, climate collapse, mass migration, societal unrest, yada yada.
What happens to all of these AI-native companies if the AI bubble is not able to survive in these conditions? If your current development process is built on the metabolic equivalent of 400kg of leaves per day[0], then when the allegorical asteroid hits, you're going to be outperformed by smaller, nimbler companies with much lower resource requirements. Those companies may be better suited for survival in hostile macro conditions.
In other words, I think a lot of companies believe that they're trimming their metabolic fat by replacing engineers with AI. Lower salary costs! But at the same time, they're also increasing their reliance on brittle energy infrastructure that may not survive this century. (Not to mention the brittleness of the semiconductor fabrication pipeline, RAM availability, etc)
> Right now there are companies which hire software devs or data scientists to just solve a bunch of random problems so that they can generate training data for an LLM model.
> Which begs questions about whether closed source will provide any protection (it doesn't appear so, given how able AI tools already are at disassembly?)
Disassembly implies that you're still distributing binaries, which isn't the case for web-based services. Of course, these models can still likely find vulnerabilities in closed-source websites, but probably not to the same degree, especially if you're trying to minimize your dependency footprint.
- Dijkstra